Edge computing system

ABSTRACT

An edge computing system comprises: a cloud computing system; an edge processing function; a connection between the edge processing function and the cloud computing system; a backend server within the cloud computing system. An assessment module is configured to receive information about processing goals, and processing capabilities of the backend server and the edge processing function. The assessment module derives a set of possible interfaces and corresponding functionality splits defining a division of processing activity between the backend server and the edge processing function. Based on a received measurement of bandwidth and/or of latency on the connection, the assessment module selects an interface and corresponding functionality split, and downloads them to the edge processing function and the backend server.

RELATED APPLICATION

This is a continuation of U.S. patent application Ser. No. 15/838,644,Filed Dec. 12, 2017, entitled EDGE COMPUTING SYSTEM, which claims thebenefit of United Kingdom Application No. 1621068.4 filed Dec. 12, 2016.The content of this application is fully incorporated herein in itsentirety.

TECHNICAL FIELD

The invention relates to application functions that can be split betweencloud and ‘edge’ computing systems.

BACKGROUND

A recent development in cloud computing is the use of ‘fog’ or ‘edge’computing. ‘Fog’ or ‘edge’ computing relies on moving computing andstorage functionality out from the cloud and closer to whatever entitiesor data is to be managed and processed. Such functionality may beapplied, for example, to the ‘Internet of Things’. ‘Internet of Things’,IoT, systems often have a wide variety of equipment designs, each ofwhich may have only limited computing power but yet may produce usefuldata. Such data often originates from widely spaced locations.

Henceforth, the term ‘edge’ computing will be used in this applicationto cover computing arrangements that are typically referred to either as‘fog’ or ‘edge’ computing by practitioners. Edge computing is describedmore fully at:http://www.etsi.org/technologies-clusters/technologies/mobile-edge-computingFog computing is described more fully at:https://www.openfbgconsortium.org/resources/#definition-of-fog-computing

FIG. 1 illustrates known cloud computing systems. In FIG. 1A, an exampleof a known cloud computing architecture 100 is shown in schematic form.A backend server 110 forms part of a cloud computing system 112. Backendserver 110 provides a backend processing function, and may for examplebe an IoT server. Connection 120 links backend server 110 to firstsensor device 140, second sensor device 144 and third sensor device 148.Connection 120 serves to provide backhaul connectivity, and is generallya direct connection. In various different versions of cloud computingarchitecture 100, the connection 120 may be provided by one or morecommunication technologies, such as cellular, WiFi or Ethernet.

In FIG. 1B, an example of a known Edge computing architecture 160 isshown in schematic form. A backend server 110 forms part of a cloudcomputing system 112. Connection 120 links backend server 110 to an edgeprocessing function 130. Connection 120 serves to provide backhaulconnectivity. Edge processing function 130 provides some of thecomputing and storage functionality from the cloud computing system 112,such as some of the functionality of the backend server 110 of FIG. 1A.Edge processing function 130 connects to first sensor device 140 viafirst connection 142, to second sensor device 144 via second connection146, and third sensor device 148 via third connection 150. First sensordevice 140, second sensor device 144 and to third sensor device 148connect to edge processing function 130, where measurements areinitially processed and then results sent to the backend functionrepresented by backend server 110.

In an illustrative example, the edge processing function 130 may belocated in the Radio Access Network of a cellular communications system.First connection 142, second connection 146 and third connection 150 aretherefore high bandwidth links with very high availability and lowlatency. Edge processing function 130, when located in the Radio AccessNetwork of a cellular communications system, may support many otherremote devices than the first sensor device 140, second sensor device144 and third sensor device 148 illustrated in FIG. 1B. Although remotefrom edge processing function 130, those devices may be part of, forexample, enterprise computing systems located in customers' premises.

The recognized benefits of the migration to edge computing are asfollows: (i) Reduced bandwidth in the backhaul link 120 to the cloudprocessing functionality in the backend server 110, which reduces thevolume of data that needs to be sent back to the cloud computing system112; (ii) Reduced latency, because the edge processing function 130 canproduce results quickly, due to the close proximity of edge processingfunction 130 to local control functions; (iii) Improved security. Theimproved security results from less data being sent to the cloudcomputing system 112. In addition, rather than having security endpointson each low power sensor node such as first sensor device 140, as is thecase in the architecture 100 of FIG. 1A, the security endpoint is at theedge processing function 130.

In all of scenarios (i)-(iii) above, the need for backend server 110 andcloud computing system 112 remains. In a simple example, based on FIG.1B, the edge processing function 130 stores the last hour's worth ofdata from first sensor device 140, second sensor device 144 and thirdsensor device 148, each of which might publish a temperature readingevery minute. Only when any individual temperature reading exceeds agiven threshold would all of the last hour's data from all of firstsensor device 140, second sensor device 144 and third sensor device 148be uploaded to the cloud computing system 112 and backend server 110 forprocessing.

One limitation in edge computing system 150 of FIG. 1B remains thereliability of backhaul link 120, even given the autonomous nature ofsome processing carried out in edge processing function 130.

SUMMARY OF THE INVENTION

In accordance with a first aspect of the invention, an edge computingsystem in accordance with claim 1 is provided. In accordance with asecond aspect of the invention, an edge processing function inaccordance with claim 6 is provided. In accordance with a third aspectof the invention, an edge computing system in accordance with claim 7 isprovided. The dependent claims provide further details of embodiments.

BRIEF DESCRIPTION OF THE DRAWINGS

Further details, aspects and embodiments of the invention will bedescribed, by way of example only, with reference to the drawings. Inthe drawings, like reference numbers are used to identify like orfunctionally similar elements. Elements in the figures are illustratedfor simplicity and clarity and have not necessarily been drawn to scale.

FIG. 1A shows an example of a known cloud computing architecture 100 inschematic form.

FIG. 1B shows an example of a known edge computing architecture 160 inschematic form.

FIG. 2 illustrates an edge computing system, in accordance with anembodiment of the present invention.

FIG. 3 provides a high level overview of the functions of theinteracting parts of the edge computing system of FIG. 2.

FIG. 4 provides more specific detail of the software developmentfunctionality of FIG. 3.

FIG. 5 illustrates an edge computing system 500, in accordance withanother embodiment of the present invention.

FIG. 6 is a flowchart that illustrates the steps of a method that can beused with the edge computing system of FIG. 5.

FIG. 7 illustrates an edge computing system 600, in accordance withanother embodiment of the present invention.

FIG. 8 illustrates one practical embodiment of an edge processingfunction that is wirelessly connected to sensors or other devices.

Skilled artisans will appreciate that elements in the figures areillustrated for simplicity and clarity and have not necessarily beendrawn to scale. For example, the dimensions and/or relative positioningof some of the elements in the figures may be exaggerated relative toother elements to help to improve understanding of various embodimentsof the present invention.

DETAILED DESCRIPTION

Example embodiments of the present invention are described below.

When designing functionality, such as for the known edge processingfunction 130 of FIG. 1B, separate development is normally required toconstruct the functionality that will reside at the edge processingfunction 130 and in backend server 110 of cloud computing system 112. Inparticular, a predefined interface is specified between these twofunctions. The interface may be an API, i.e. an Application ProgrammingInterface. In known systems, the interface ensures that edge processingfunction 130 and cloud computing system 112 can talk to each othereffectively. Typically, software designers will first of all decide on abespoke interface design for the interface between edge processingfunction 130 and cloud computing system 112. That design might depend ona ‘worst-case’ scenario of the bandwidth of connection 120. Once thebespoke interface design has been frozen, typically, separatedevelopment groups will then have to develop the edge and network sideof the functionality within the constraints set by the chosen interface.

The designers of an interface between edge processing function 130 andcloud computing system 112 of FIG. 1B thus make fixed, a prioriassumptions about the bandwidth available and/or the latency inconnection 120, i.e. in the backhaul link between cloud computing system112 and edge processing function 130. These assumptions then determine asplit of functionality that the designers will implement between edgeprocessing function 130 and cloud computing system 112. In the exampleof FIG. 1B, if it is assumed that the bandwidth in the connection 120 ishigh, a scheme might be implemented as discussed previously, wherebyonce a temperature threshold is crossed the whole of, for example, anhour's data from first sensor device 140, second sensor device 144 andthird sensor device 148 is transported back to cloud computing system112. Alternatively, when the assumption about the bandwidth available inconnection 120 is that that bandwidth is deemed to be low, then thedesigners might arrange the interface such that, once the threshold isreached, only a processed version of the hour's data is sent to thecloud computing system 112. For example, a distribution function may becalculated in edge processing function 130 based on the ensemble of dataover a time period. Then raw versions of only those data which areoutliers may be provided to cloud computing system 112 via connection120.

Typically backhaul connections such as connection 120 have capacitywhich is difficult to predict and may vary considerably over time. Thisleads to the a priori assumptions in known systems, which then guide thedesigners of the edge and cloud-side elements to design specificfunctionality for the edge and cloud elements.

In contrast to the situation in FIG. 1B, the present invention startsfrom realizing the limitations of such known approaches. The inventionaddresses situations that may arise in which a priori assumptions aboutthe backhaul connections are wrong or at best inefficient. In suchsituations, without the invention, there may be congestion in connection120 when sending back data to cloud computing system 112. Alternatively,unnecessarily large processing may be conducted at the edge processingfunction 130, and some useful data is then not used in the overallprocessing, including that in backend server 110. A similar argument canbe made regarding latency in the backhaul, which leads in known systemsto similar non-optimal processing.

A first embodiment of the invention is generally as illustrated in FIG.2. FIG. 2 illustrates an edge computing system 200, in accordance withan embodiment of the present invention. Backend server 250 forms part ofcloud computing system 252.

Edge processing function 260 links to cloud computing system 252 viaconnection 262. Edge processing function 260 links to first sensordevice 270 via first connection 272, to second sensor device 274 viasecond connection 276, and to third sensor device 278 via thirdconnection 279.

Edge processing function 260 may, for example, be implemented in an edgeserver, or another module provided with a processor, such as a digitalsignal processor (DSP). Although henceforth referred to with the generalterm ‘edge processing function’ 260, a hardware implementation ofcircuitry to achieve the required functionality is intended, and adetailed hardware implementation is described in connection with FIG. 8.Where edge processing function 260 is a wireless device, the availablebattery power to edge processing function 260 may be an issue. Inparticular, an assessment of a battery cost of sending data over thebackhaul link, i.e. connection 262, and/or a battery cost of performingprocessing at edge processing functionality 260, may be utilised in thepresent invention.

At data input module 210, the overall goals of the processing are setout. Examples of these are given below. Arrow 212 indicates that theseoverall goals are provided as an input to an assessment module 220.Arrow 214 indicates that a second input is provided to assessment module220 by a measurement of connection 262, i.e. the backhaul link as it ismeasured empirically. Assessment module 220 comprises a processor 214,memory 216 and a communication processor 218. Communication processor218 receives inputs 212 and 214, and communicates outputs fromassessment module 220 as described below.

Assessment module 220 carries out two specific actions. The first actionis to determine interfaces, each with a corresponding split offunctionality between backend server 250 and edge processing function260. The second, subsequent action is to supply a suitable interface anda corresponding split of functionality to a backend server 250 and anedge processing function 260, after assessment module 220 has receivedinformation about communication conditions between the backend server250 and the specific edge processing function 260.

The interfaces that are developed within assessment module 220 areillustrated in processing stack 290 of FIG. 2, which is illustratedseparately from assessment module 220 for clarity of illustration.Processing stack 290 is illustrated as having multiple interfaces, i.e.first interface 222, second interface 224 and third interface 226. Eachinterface has a corresponding division of functionality between thebackend server 250 and edge processing function 260. The higher inprocessing stack 290 the interface is shown, then: (i) the moreprocessing is required at the edge processing function 260 when thatinterface is used; and (ii) the smaller the bandwidth required onconnection 262, i.e. the backhaul link, or the greater the tolerance tolatency delay, when that interface is used.

A subsequent stage of operation is shown in processing stack 292. Inprocessing stack 292, arrow 214 illustrates again the second input toassessment module 220 that is provided by a measurement of connection262. In the exemplary illustration of processing stack 292, arrow 214points to first interface 222, which is the lowest interface inprocessing stack 292. Based on the overall goals 210 of the processingand the measurement shown by arrow 214, first interface 222 will beprovided to backend server 250 and edge processing function 260,together with a corresponding specification of processing to be carriedout by each of backend server 250 and edge processing function 260.Arrow 240 indicates communication of the definition of first interface222 to backend server 250, together with a definition of the processingthat backend server 250 is to carry out in order to meet overall goals210. Arrow 242 indicates communication of the definition of firstinterface 222 to edge processing function 260, together with adefinition of the processing that edge processing function 260 is tocarry out in order to meet overall goals 210.

If the measurement 214 comprised different values, then the interfacesupplied to each of backend server 250 and edge processing function 260might not be first interface 222. Second interface 224 and thecorresponding functionality, or third interface 226 and thecorresponding functionality, might instead be appropriate.

Thus assessment module 220 serves to automatically derive, and thendeliver, a partition of functions between backend server 250 of cloudcomputing system 252 and edge processing function 260. The deliveryindicated by arrows 240 and 242 is based on actual measurement 214 ofthe backhaul capacity and/or latency of connection 262.

In a further enhancement, other cost functions may be incorporated aspart of the decision process, such as the power requirement forprocessing in edge processing function 260 and/or for communication overconnection 262. Where edge processing function 260 exists in a mobiledevice, battery demands on the mobile device may be a constraint that isused, in addition to or in some instances instead of the measurements ofthe backhaul capacity and/or latency of connection 262. The total listof factors that assessment module 220 is configured to utilize, ifavailable, comprises the following: (i) Backhaul bandwidth; (ii)Backhaul latency; (iii) Storage capability at the edge processingfunctionality 260; (iv) Processing capability at edge processingfunctionality 260; (v) Battery cost of sending data over the backhaullink, i.e. connection 262; (vi) Battery cost of performing processing atedge processing functionality 260. Each of these would be weighted, ifavailable, but would determine the functional split that would bechosen.

The invention thus provides a tool to develop interfaces, such as firstinterface 222, second interface 224 and third interface 226. These areinterfaces, and corresponding functionality splits, which take the inputfrom step 210 and provide solutions that meet the overall goals of theprocessing function. The work of assessment module 220 is illustratedbelow with a numerical example. In the example, we can consider a largenumber of temperature sensors associated with a manufacturing process.The temperature sensors produce readings every 2 seconds. An overallgoal specified in step 210 is to shut down production when both of thefollowing two conditions are met: (i) At least two sensors show atemperature greater than 20 degrees within a 30 second period; and (ii)The 95th percentile of the distribution of all data collected over a oneweek period is greater than 10 degrees. These are inputs into assessmentmodule 220, which constitutes a software tool that defines the overallfunctionality that the combined edge/cloud function must achieve. Thetable below shows examples of the possible functional splits that thesoftware tool may produce for the numerical conditions (i) and (ii)above. The functional splits in the table also define the structure ofthe interface between cloud and edge.

As an example, the split in the first row of the table is appropriate ifthe battery cost of using the backhaul is high but the battery cost ofedge processing is low. This split would also be appropriate for thecase of low backhaul bandwidth and high latency. In this case processingat edge processing function 260 is appropriate. Row 1 is thus onepossible interface and corresponding optimum split of functionalitybetween edge processing function 260 and backend server 250 with all theprocessing being implemented in first edge processing function 260. Inthis case, the interface would allow for information to pass back tobackend server 250. The processed data sent to the server 250 would be,for example, a simple indication to the cloud that the alarm conditionhas fired. Server 250 would then not have the data on which to performsome form off line analytics later. The alarm condition might be sentdirectly to a local function rather than the cloud which would totallyremove cloud functionality.

Notably, the backend server 250 would still have inbuilt processingcapability, which might be used for example with other edge processingfunctions. The inbuilt processing capability of the backend server 250might also be used subsequently, after a change is made to the design ofedge processing function 260 or to the sensors or the process that thesensors monitor, at which point a new cycle of design of the interfaceand split of functionality between edge processing function 260 andbackend server 250 should be made.

TABLE 1 Illustrative example of operation of assessment module Possiblefunctional split Detail of operation Comment 1. Do all processing at Theinterface between the The advantage of this split is that the the edgeprocessing edge processing function backhaul bandwidth requirements arefunction 260. 260 and backend server low. However significant storage250 is just a simple binary capability is required at edge trigger,based on whether processing function 260, i.e. a whole the condition toshut week's data needs to be stored. Also, by down production has or notsending any data to backend server has not occurred. 250, the chance toperform offline analytics on the data to find other issues is lost. 2.Store 30 s worth of The core then uses the The advantage of this is thatthe edge data at the edge 30 s distribution to create processor canquickly determine processing function a 1 week distribution, andcondition (i) and the processed 30 s data 260 and perform test thus candetermine if requires a relatively small backhaul for condition (i);also condition (ii) occurs. The bandwidth. The edge processor requirescalculate the core is informed of a relatively small data storage.distribution of the 30 s trigger for condition (i) However, only alimited amount of data and send an directly. The interface is offlineanalytics can be performed on indication of this then defined as binarythe data, because of the processing at distribution to the core. triggerfor condition (i), the edge processing function 260. and an indicationof the distribution for a 30 s period. 3. Store 30 s worth of Theinterface is then The advantage of this is that the edge data at theedge defined as binary trigger processing function 260 can quicklyprocessing function for condition (i) and a set determine condition (i).By packing up 260 and perform test of 30 s worth of raw data. 30 s worthof data, it is likely to be for condition (i); also possible to reducethe required send the 30 s worth of bandwidth on connection 262, evendata unprocessed to the though raw data is being transmitted. backendserver 250. However bandwidth requirements on connection 262 are high.4. The edge processing function 260 sends raw data to the backend server250. No functionality is required of edge processing function 260.

As shown in table 1 above, the software development tool has generatedmultiple interface and corresponding functionality splits. Solutionssuch as those shown in table 1 are set up in processing stack 290 inadvance. The example of table 1 illustrates the ‘automatic’ nature ofthe invention.

The subsequent step performed by assessment module 220 is to compare themeasurement indicated by arrow 214 with the multiple interfaces andcorresponding functionality splits. The measurement may include, forexample, bandwidth and latency, plus the available processing andstorage capability of the edge processing functionality 260.

There may be multiple edge processing functionalities 260 at differentlocations throughout edge computing system 200. In this case, themultiple edge processing functionalities 260 may therefore be suited todifferent partitions, even when working with the same backend server250. The example of table 1 illustrates the ‘automatic’ nature of theinvention.

Thus the partitioning of functions may be implemented by having multipledesigns of interface available, in advance, before any selection needsto be made of which interface is to be provided to one or more edgeprocessing functions 130. Based on actual measurements 214 of thebackhaul capacity and/or latency of connection 120, a selection is thenmade of which interface is to be provided to edge processing function130 to run the backhaul communication over connection 120. Correspondingfunctionality is provided in backend server 250 to work with theparticular interface that has been provided to edge processing function130 to run the backhaul communication over connection 120 to backendserver 250.

The invention is thus to have a single definition of the overallprocessing problem and a function which automatically partitionsfunctionality. The single definition of the overall processing problemensures that the overall software design, which encompasses both cloudand edge processing, is based on a single set of goals.

In another simplified example of temperature sensing, we may havetemperature sensors in a factory process. That process may have to behalted for a period of time, if the first sensor device 140, secondsensor device 144 and/or third sensor device 148 detect particulartemperature values. The invention may aim, for example, to analyse thestate of all temperature readings, to test for a potential productionproblem when any one of the temperature sensors exceed a giventhreshold. However, there is also a proviso that the data must beanalysed in a very short period of time after the threshold has beenexceeded, say less than 10 ms. If a static version of the interface wereto be defined, as with the known system of FIG. 1B, then a designdecision would need to be taken at the outset on the appropriate splitin functionality between cloud and edge processing, based on an off lineestimate of the latency and bandwidth of the connection 120, i.e. thebackhaul link. In the known system of FIG. 1B, the software designersmight typically assume that the worst case latency and/or bandwidth inthe connection 120 is poor, so that the functionality in the edge is tomonitor the temperature readings and when the threshold is exceeded ahighly processed set of data (say the mean and standard deviation of allthe temperature readings) should be passed up to the cloud forprocessing. In the backend server 110 of FIG. 1B, a model of theproduction process checks if this communicated data is indicative of anacceptable process. Because the cloud functionality of FIG. 1B has towork on a highly processed set of data, the decision whether there is aproblem isn't as accurate, so a more conservative production process hasto be maintained, with the production line frequently shut down.

With the invention, without reliance on the assumptions of knownsystems, then, for example, the processing at the edge may need to beless intensive. In the example discussed above, with the invention, rawmeasurements for the highest readings from 10 sensors plus the mean andstandard deviation may then be provided to the cloud processor in theavailable time. The result is better overall functionality. In the caseof first sensor device 140, second sensor device 144 and/or third sensordevice 148 detecting particular temperature values of an industrialprocess, the result would be that the production line is shut down lessfrequently.

There may be other factors besides bandwidth and latency of connection120 that are measured and fed to the decision methodology, and whichthus affect the resulting design. For instance, it may require largeamounts of power to send data over the backhaul link and the edgeprocessor may have only limited battery capabilities.

In the method of a first embodiment of the present invention, there maybe multiple pre-stored interfaces. The method adaptively chooses whichlevel of interface to supply to the edge and cloud processing elements,to run over the backhaul such as connection 120.

The embodiment of FIG. 2 shows a single edge processing function 260.Where multiple edge processing functions 260 are to work with backendserver 250, each edge processing function 260 may be provided with aninterface that is based on the bandwidth and/or latency of theconnection 262 that is available between that particular edge processingfunction 260 and cloud computing system 252.

The measurement of the connection 120 may be a single, one-timemeasurement. However, the measurement may itself comprise or be derivedfrom multiple sub-elements of the measurement, with the sub-elementscomprising at least one of latency and bandwidth. The measurement may bederived from an ‘active sounding’. For example, sounding data is sentfrom cloud computing system 252 to edge processing function 260 and/orvice versa. The sounding data may then be used to determine both latencyand bandwidth. Alternatively, the measurement may be a directmeasurement of one or more physical layer parameters, e.g. themodulation and coding scheme employed in LTE or 802.11 WiFi. Theprocessing functionality for edge processing function 260 and backendserver 250 are chosen together with the interface that is to be used. Asa consequence, this choice may not fully utilize the processingcapability that is available in one or both of edge processing function260 and backend server 250. However, a different measurement of theconnection 120, for example at a different time, may lead to aninterface and split of processing functions between edge processingfunction 260 and backend server 250 that fully utilizes the maximumavailable processing capacity in one or both of edge processing function260 and backend server 250. In effect, a software development tool mayallow the automated design of, and/or the selection of one of, firstinterface 222, second interface 224 and third interface 226 with anoptimised split of functionality.

FIG. 3 provides a high level overview of the functions of theinteracting parts of the edge computing system 200 of FIG. 2. Thefunctions in FIG. 3 are illustrated by being linked in FIG. 3 in thetemporal sequence in which they occur.

At step 310, the overall process and design goals are set up, as shownat 210 in FIG. 2. The overall process and design goals are supplied tothe software development functionality of assessment module 220 at step320.

At step 330, various input information is fed into the method 300. Theparameters supplied at step 330 are some or all of (i) Storage capacityof edge processor; (ii) Processing capacity of edge processor; (iii)Battery cost of sending data over backhaul; and (iv) Battery cost ofperforming edge processing. As more comprehensive list of parameters canbe used at step 330 when other information is available about the designof either connection 262 or one or more of edge processing functionality260 or backhaul server 250. For example, when the backhaul bandwidth andbackhaul latency are known, they can also be used in step 330.

At step 340, a set of options for interface design, with correspondingfunctionality splits, is created. Software development functionality 320derives the first interface 222, second interface 224 and thirdinterface 226, as shown at 290 in FIG. 2. Software developmentfunctionality 320 derives an optimised split of functionality that willwork with each of first interface 222, second interface 224 and thirdinterface 226, i.e. that would be applied between edge processingfunction 260 and backend server 250 if the particular interface wereapplied. The options might, instead, be the four options in table 1above.

The bandwidth and latency measurement 350 provides input information tomethod 300, concerning the bandwidth and/or latency in the connection262. Based on the measurement, at step 360 the software developmentfunctionality 320 is then able to choose one of the first interface 222,second interface 224 or third interface 226, and send it to the softwareimage reception functionality 370.

Software image reception functionality 370 in each of backend server 250and edge processing function 260 receives the software image from thedevelopment tool and installs it at step 380 in edge processing function260 and backend server 250. The generic processing functionality in eachof edge processing function 260 and backend server 250 runs the softwareimage, i.e. the chosen interface and appropriate supporting processingtasks.

FIG. 4 is a flowchart that illustrates, at a high level, the steps ofthe method used to derive and distribute the first interface 222, secondinterface 224 or third interface 226. Thus FIG. 4 provides more specificdetail of the software development functionality utilized at steps 320and 330 in FIG. 3.

At step 410, the overall functionality that must be delivered by theedge processing function 260 and backend server 250 is derived. Thisdecision is based on the overall goals in box 210 of FIG. 2. A furtherinput to the decision is obtained in step 420, where the measurement 214from connection 262 is obtained. In step 430, the cloud functionality tobe implemented in backend server 250 is created and sent to backendserver 250. In step 430, the edge functionality to be implemented inedge processing function 260 is created and sent to edge processingfunction 260.

In FIG. 4, the order of steps 410 and 420 could be reversed, or both ofsteps 410 and 420 could be implemented in parallel. Likewise, the orderof steps 430 and 440 could be reversed, or both of steps 430 and 440could be implemented in parallel.

FIG. 5 illustrates an edge computing system 500, in accordance withanother embodiment of the present invention. The overall goals of theprocessing to be achieved are shown at 510, and are fed to assessmentunit 520. Assessment unit 520 creates processing stack 521. Withinprocessing stack 521 are first interface 522, second interface 524 andthird interface 526.

The edge computing system 500 further comprises cloud computing system552, connection 562, backend server 550 and edge processing function560. Arrow 540 indicates download from processing stack 521 to backendserver 550. Arrow 542 indicates download from processing stack 521 toedge processing function 560. The whole of the processing functionality,including all of the possible interfaces and functionality splits inprocessing stack 521, can be downloaded to both edge processing function560 and backend server 550.

With edge computing system 500, the functionality required to meet theoverall processing goals is downloaded in its entirety to both the edgeprocessing function 560 and the backend server 550. During subsequentoperation of the edge computing system 500, the edge processing function560 and the backend server 550 then adaptively choose the interfacelevel and the appropriate functionality that each must perform. Dashedarrow 280 indicates the communication and decision made between edgeprocessing function 560 and backend server 550. Those choices are madein dependence on a measurement of conditions in the connection betweenthe edge processing function and cloud computing system. Hence the splitof functionality between the edge and cloud devices, and the selectionof the appropriate interface between the devices, are variable atdifferent times in dependence on prevailing conditions in the backhaulconnection.

The edge computing system 500 of FIG. 5 differs from the edge computingsystem 200 of FIG. 2 in two aspects. The first difference concerns thedownload to edge processing function 560 and backend server 550. Atleast two interfaces and corresponding splits of functionality aredownloaded from the processing stack 521 to each of edge processingfunction 560 and backend server 550. Arrow 540 indicates download fromprocessing stack 521 to backend server 550. Arrow 542 indicates downloadfrom processing stack 221 to edge processing function 260. In a moregeneral case, the whole of the processing functionality, including allof the possible splits, can be downloaded to both edge processingfunction 560 and backend server 550. After downloading the whole of thefunctional stack with all splits/interfaces to each of edge processingfunction 560 and backend server 550, edge processing function 560 andbackend server 550 then determine the split between themselves, whichmay be a partly off line function.

The second difference concerns decisions that will be made between edgeprocessing function 560 and backend server 550, after they have receivedthe at least two interfaces and corresponding splits of functionalityfrom the processing stack 521. Dashed arrow 280 indicates thecommunication between edge processing function 560 and backend server550, and edge processing function 560 and backend server 550 cantherefore decide, adaptively, which interface level is to be used. Thedecision can be based on a realtime measurement of connection 262. Thatmeasurement can correspond to a real-time, ongoing measurement of thesame variables as were measured to provide measurement 214 in FIG. 2.

Arrow 214 is not shown in FIG. 5, because the measurement is not used toderive first interface 522, second interface 524 and third interface 526in assessment module 520. Assessment module 520 simply determinespossible interfaces and corresponding functionality for each interface.When two or more of first interface 522, second interface 524 and thirdinterface 526 have been downloaded to edge processing function 560 andbackend server 550, with the corresponding functionality, then one ofthe interfaces will be selected. However, subsequent measurements ofconnection 562 may indicate that a different interface would provide amore optimum operation, i.e. would better meet the overall goals 510under prevailing conditions in connection 562. When that occurs,connection 580 allows a joint decision to be made by edge processingfunction 560 and backend server 550 to use a different interface.

One or both of edge processing function 560 and backend server 550 hasmeasurement functionality to support the measurement of bandwidth and/orlatency. Each of edge processing function 560 and backend server 550 hasfunctionality to allow it to select a different interface and split offunctionality than is currently being applied within it, by agreementbetween the edge processing function 560 and backend server 550.

FIG. 6 is a flowchart that illustrates the steps of a method that can beused with edge computing system 500 of FIG. 5.

In step 610 the overall functional requirements are defined. Thiscorresponds to step 410 in FIG. 4. In step 620, assessment module 520creates the functionality. This functionality defines interfaces andcorresponding splits of functionality between edge processing function560 and backend server 550 that are to be sent to edge processingfunction 560 and backend server 550. The interfaces and correspondingsplits of functionality between edge processing function 560 and backendserver 550 then may later be selected by edge processing function 560and backend server 550, as appropriate.

Subsequently, at step 630, edge processing function 560 and backendserver 550 measure properties of the connection 562. The measurement maycomprise bandwidth and/or latency.

At step 640, edge processing function 560 and backend server 550 jointlydecide on an interface and the corresponding functionality split betweenthem. If they are already in operation, they may decide either tomaintain or to change the interface the corresponding functionalitysplit that they are already using.

In step 650, a corresponding measurement to that in step 630 is made. Ifthe bandwidth and/or latency have changed, for example by crossing apreset threshold, then the method moves to step 660. At step 660, theedge processing function 560 and backend server 550 jointly decideeither to maintain or to change the interface that they are using, andthe corresponding functionality split between them. If step 650 detectsno change, or a change in latency and/or bandwidth below a threshold,then the method loops back to step 650 again.

In an alternative embodiment of the method of FIG. 6 and edge computingsystem 500 of FIG. 5, information concerning likely bandwidth andlatency on connection 562 is used to create the functionality. Thus step620 involves deriving interfaces and corresponding splits offunctionality between edge processing function 560 and backend server550 that are more likely to be optimized to bandwidth and/or latencythat will be encountered by the edge computing system 500. Theinformation concerning likely bandwidth and latency on connection 562may be derived in a variety of ways. For example, it can be based onhistorical measurements, present values, or predictions based on likelyload/activity levels in future.

FIG. 7 illustrates an edge computing system 600, in accordance withanother embodiment of the present invention. Edge computing system 600corresponds generally to edge computing system 500 of FIG. 5. However,the whole set of functionality of processing stack 621 is notdownloaded. Instead, only parts of the functionality of processing stack621 is downloaded, i.e. the parts which the edge and cloud functionalitydynamically choose the appropriate split. In general terms, the toplevel functionality is deemed too intensive for the edge processingfunction and the backend cloud function is not to be provided withfunctionality for direct interfacing to measurement nodes.

In FIG. 7, the downloads indicated by arrows 640 and 642 do not includethe whole set of functionality from processing stack 621. Instead, thedownloads indicated by arrows 640 and 642 may be limited to those partsof the functionality between which the edge processing function 660 andbackend server 650 will choose dynamically. So edge processing function660 and backend server 650 store those parts of the functionality thatthey always use, and those parts of the functionality that they will useunder certain conditions on connection 662 in dependence on themeasurement of connection 662.

In FIG. 7, the backend server 650 is not provided with the lowest levelsof processing functionality, for example processing functionality toallow backend server 650 to deal with the direct interfacing tomeasurement nodes such as first sensor device 670, second sensor device674, and third sensor device 678. The lowest levels of functionalityheld in processing stack 621 are indicated by double-headed arrow 627.The levels of functionality in processing stack 621 that are indicatedby double-headed arrow 627 are not sent to backend server 550. Thesubset of functionality of processing stack 621 that will be transmittedto backend server 650 is indicated on FIG. 7 by sub-stack 630 at theupper centre of FIG. 7. Sub-stack 630 lacks any functionality belowlevel 622.

In FIG. 7, the edge processing function 560 is not be provided with thehighest levels of processing functionality. The highest levels offunctionality held in processing stack 621 are indicated bydouble-headed arrow 628. The levels of functionality in processing stack621 that are indicated by double-headed arrow 628 are not sent to edgeprocessing function 660. The subset of functionality of processing stack621 that will be transmitted to edge processing function 660 isindicated on FIG. 7 by sub-stack 632 at the lower centre of FIG. 7.Sub-stack 632 lacks any functionality above level 626.

In the embodiment of FIG. 7, each of edge processing function 660 andbackend server 650 will receive the processing functionality thatassessment module considers that each will always need, plus the‘variable’ functionality that each may choose to implement in dependenceon the measurement of the connection 662. Dashed arrow 680 indicatesonce again a communication and decision made in real time between edgeprocessing function 660 and backend server 650 about which parts of theselectable functionality to employ.

FIG. 8 illustrates one practical embodiment of an edge processingfunction that is wirelessly connected to sensors or other devices.

Referring now to FIG. 8, an example of edge processing function 800 asmodified by the functionality herein described, is illustrated inaccordance with some example embodiments of the present invention. Inexample embodiments of the invention the edge processing function 800has been modified with the addition of functionality as described withreference to FIGS. 2-7. In practice, purely for the purposes ofexplaining embodiments of the invention, the edge processing function800 is described in terms of both a wireless communication device and awireline connected device, such as a computer, network server, laptop,etc.

In a wireless embodiment, the edge processing function 800 contains oneor more antenna(e) 802 for communicating via various wirelesstechnologies. In one example, the one or more antenna(e) 802 (coupledvia a wireless interface 808 with associated transmit and receivecircuitry) is configured to radiate and receive radiated signals 832,for example, on WiFi™ frequencies or bluetooth BT™ frequencies orcellular frequencies, e.g. LTE™ over a cellular network (not shown).

In a wireless example, the one or more antenna(e) 802 is coupled to anantenna switch or duplexer 804 that provides isolation between receiveand transmit chains within the edge processing function 800, as well asproviding isolation between circuits targeted for the specifictechnologies being supported, e.g. LTE™, WiFi™, BT™. One or morereceiver chains, as known in the art, include receiver front-endcircuitry 806 (effectively providing reception, filtering andintermediate or base-band frequency conversion). The receiver front-endcircuitry 806 is coupled to a signal processor 828 (generally realizedby a digital signal processor (DSP)). A battery 830 is provided.Although shown connected to processor 828, battery 830 may provide allpower to edge processing function 800 in as wireless example.

A skilled artisan will appreciate that the level of integration ofreceiver circuits or components may be, in some instances,implementation-dependent. A controller 814 maintains overall operationalcontrol of the edge processing function 800. The controller 814 is alsocoupled to the receiver front-end circuitry 806 and the signal processor828. A timer 818 is operably coupled to the controller 814 to controlthe timing of operations, e.g. transmission or reception oftime-dependent signals, within the edge processing function 800.

In this example, controller 814 is connected to an internet protocol(IP) circuit/function 811, which is coupled to one or more IP routingtables and/or routing protocol software 812. In a wireline sense, thecontroller 814 may be operably coupled to other devices and nodes via awireline interface 809 using a wireline connection 810, such asEthernet.

A store 816 for processing functions is connected to signal processor828. In some examples, the signal processor 828 of the edge processingfunction 800 may encompass much more functionality than the IPcircuit/function 811 and IP routing tables and/or routing protocolsoftware 812. In particular, in some examples, it is assumed that signalprocessor 828 may handle some or all higher layer functionality.

Thus, a method and apparatus for improving the reliability andperformance of an edge computing system have been described, where theaforementioned disadvantages with prior art arrangements have beensubstantially alleviated.

It will be further appreciated that, for clarity purposes, the describedembodiments of the invention with reference to different functionalunits and processors may be modified or re-configured with any suitabledistribution of functionality between different functional units orprocessors is possible, without detracting from the invention. Forexample, functionality illustrated to be performed by separateprocessors or controllers may be performed by the same processor orcontroller. Hence, references to specific functional units are only tobe seen as references to suitable means for providing the describedfunctionality, rather than indicative of a strict logical or physicalstructure or organization.

Aspects of the invention may be implemented in any suitable formincluding hardware, software, firmware or any combination of these. Theinvention may optionally be implemented, at least partly, as computersoftware running on one or more data processors and/or digital signalprocessors. For example, the software may reside on non-transitorycomputer program product comprising executable program code to increasecoverage in a wireless communication system.

Thus, the elements and components of an embodiment of the invention maybe physically, functionally and logically implemented in any suitableway. Indeed, the functionality may be implemented in a single unit, in aplurality of units or as part of other functional units. Those skilledin the art will recognize that the functional blocks and/or logicelements herein described may be implemented in an integrated circuitfor incorporation into one or more of the communication units.

Furthermore, it is intended that boundaries between logic blocks aremerely illustrative and that alternative embodiments may merge logicblocks or circuit elements or impose an alternate composition offunctionality upon various logic blocks or circuit elements. It isfurther intended that the edge computing system and its elementsdepicted herein are merely exemplary, and that in fact many other edgecomputing systems and elements or architectures can be implemented thatachieve the same functionality.

Although the present invention has been described in connection withsome example embodiments, it is not intended to be limited to thespecific form set forth herein. Rather, the scope of the presentinvention is limited only by the accompanying claims. Additionally,although a feature may appear to be described in connection withparticular embodiments, one skilled in the art would recognize thatvarious features of the described embodiments may be combined inaccordance with the invention. In the claims, the term ‘comprising’ doesnot exclude the presence of other elements or steps.

Furthermore, although individually listed, a plurality of means,elements or method steps may be implemented by, for example, a singleunit or processor. Additionally, although individual features may beincluded in different claims, these may possibly be advantageouslycombined, and the inclusion in different claims does not imply that acombination of features is not feasible and/or advantageous. Also, theinclusion of a feature in one category of claims does not imply alimitation to this category, but rather indicates that the feature isequally applicable to other claim categories, as appropriate.

Furthermore, the order of features in the claims does not imply anyspecific order in which the features must be performed and in particularthe order of individual steps in a method claim does not imply that thesteps must be performed in this order. Rather, the steps may beperformed in any suitable order. In addition, singular references do notexclude a plurality. Thus, references to ‘a’, ‘an’, ‘first’, ‘second’,etc. do not preclude a plurality.

The invention claimed is:
 1. An edge computing system, comprising: acloud computing system, a backend server within the cloud computingsystem, an edge processing function circuit, and a connection betweenthe edge processing function circuit and the cloud computing system; anassessment module circuit, the assessment module circuit configured to:create, appropriate to a first measurement of bandwidth and/or oflatency on the connection, a first application programming interface,API, create, corresponding to the first API, first functionality for theedge processing function circuit and first functionality for the backendserver; and create, appropriate to a second measurement of bandwidthand/or of latency on the connection, a second API, create, correspondingto the second API, second functionality for the edge processing functioncircuit and second functionality for the backend server; download thefirst and second API to both the edge processing function circuit andthe backend server; download, to the edge processing function circuit,the first and second functionality for the edge processing functioncircuit, corresponding to the first and second APIs; download, to thebackend server, the first and second functionality for the backendserver, corresponding to the first and second APIs; the edge processingfunction circuit and/or the backend server being configured to select anAPI and corresponding functionality based on their respective processinggoals and processing capability.
 2. The edge computing system of claim1, wherein the edge processing function circuit is configured to: (i)receive a measurement of bandwidth and/or of latency on the connectionand a derived corresponding functionality split between the edgeprocessing function circuit and the backend server; and (ii) select thefirst or second API and corresponding first and second functionality forthe edge processing function circuit, in dependence on the measurementof bandwidth and/or of latency on the connection and the derivedcorresponding functionality split.
 3. The edge computing system of claim1, wherein the backend server is configured to: (i) receive ameasurement of bandwidth and/or of latency on the connection and aderived corresponding functionality split between the edge processingfunction circuit and the backend server; and (ii) select the first orsecond API and corresponding first and second functionality for thebackend server, in dependence on the measurement of bandwidth and/or oflatency on the connection and the derived corresponding functionalitysplit.
 4. The edge computing system of claim 1, wherein: the backendserver and edge processing function circuit are configured to worktogether to select the first or second API, in dependence on ameasurement of bandwidth and/or of latency on the connection, theirrespective processing goals and processing capability, and derivedcorresponding functionality splits.
 5. The edge computing system ofclaim 4, further comprising: one of the backend server and edgeprocessing function circuit receiving the measurement of bandwidthand/or of latency on the connection and the derived correspondingfunctionality splits.
 6. The edge computing system of claim 1, furthercomprising: the assessment module circuit being further configured toreceive information about a battery cost of sending data over theconnection, for a battery of the edge processing function circuit. 7.The edge computing system of claim 1, further comprising: the assessmentmodule circuit being further configured to receive information about abattery cost of performing processing at the edge processing functioncircuit, for a battery of the edge processing function circuit.
 8. Theedge computing system of claim 1, wherein: the assessment module circuitfurther comprises a software development functionality for deriving thefirst and second APIs and corresponding functionality splits; and asoftware image reception functionality in the edge processing functioncircuit configured to receive the first and second APIs andcorresponding functionality splits for the edge processing functioncircuit; and a software image reception functionality in the backendserver configured to receive the first and second APIs and correspondingfunctionality splits for the backend server.
 9. The edge computingsystem of claim 1, further comprising: the assessment module circuitbeing configured to receive information concerning bandwidth and/orlatency on the connection, and using the information to derive APIs andcorresponding splits of functionality between the edge processingfunction circuit and backend server.
 10. The edge computing system ofclaim 9, wherein: the received information concerning bandwidth andlatency on the connection is based on historical measurements, presentvalues, and/or predictions based on future load or activity levels.